Early Venture Evolution PDW презентация

Quick overview – 2 studies Early stage – MOOC randomized experiment Later stage – Stanford alumni data

Слайд 1Early Venture Evolution PDW
Chuck Eesley (Stanford University)
Lynn Wu (U. Penn –

Wharton)
Wesley Koo (Stanford University)
David Hsu (U. Penn – Wharton)

Слайд 2Quick overview – 2 studies
Early stage – MOOC randomized experiment

Later stage

– Stanford alumni data

Слайд 3Visions, Entrepreneurial Adaptation and Social Networks: Evidence from a Randomized Experiment

on a MOOC Platform

Charles Eesley (Stanford)
Lynn Wu (Wharton)


Слайд 4Early-stage programs
Accelerator and incubator programs outside of universities, such as YCombinator,

TechStars and the Founder Institute


National Science Foundation has recently launched an $18M program to pair select engineers and scientists who win SBIR grants with mentors and to teach them a more adaptive process for startup creation (I-Corps)

Слайд 5Difficult to Observe Entrepreneurial Processes
Planning Approach
Create an unwavering vision
Persistent in executing

the vision
Less likely to modify the vision to leverage newly available resources
Delmar and Shane, 2003; Porter, 1980

Adaptive Approach

Take adv. of new resources and change the vision if necessary
Suitable in uncertain environment such as early stage entrepreneurship?
(Baker and Nelson 2005, Blank 2013, Brown and Eisenhardt 1997, McGrath 2010)


Слайд 6Networks & Entrepreneurial Strategy
Adaptive & Network Diversity
Mentor with diverse networks offers

new and novel information and opportunities.
Adaptive entrepreneurs are likely to take advantage of the new resources.

Planning & Network Diversity

Entrepreneurs would not always use the resources from a mentor unless it conforms with the original vision.
A mentor in a cohesive network may collaborate better with the entrepreneur.


Слайд 7Networks & Entrepreneurial Strategies
Difficult to observe endogenous matching process between mentors

and mentees.
Difficult to alter coworker and friendship ties.
Difficult to observe the process of entrepreneurship.
Randomized experiments could help.

Слайд 8Setting & Data
NovoEd class: Technology Entrepreneurship
Class offered: Fall 2013 for 8

weeks
Free to anyone
Students in 61 countries in the world
Goal: Create a video pitch at the end of the class

Слайд 9Summary Statistics


Слайд 10Did the Treatment Work?



Слайд 11Treatment Effects On Outcomes








Слайд 12Mentors and Performance




Слайд 14Effects of Strategic Change on Venture Performance: The Implications of Change

Location, Level and Top Management Team Composition   Charles Eesley Stanford University David Hsu Wharton School, Management Department, University of Pennsylvania Wesley Koo Stanford University

Слайд 15Stanford Alumni Data
Survey of 143,482 individuals—all living Stanford alumni, current faculty

and selected (research) staff—to explore the influence of education on life and career choices.

Responses were received from 27,780 individuals, for a response rate of 19.5 percent.
These numbers are the percentage of respondents out of the total number in that category who received the email.
Women: 19%
Men: 19%
Business: 23%
Earth Sciences: 30%
Education: 30%
Engineering: 22%
Law: 20%
H&S: 13%
Medicine: 27%

Слайд 19Conclusion
Contrary to work on discovery-driven planning, “lean startup”, we find that

at the early stages, a planning approach appears to be more effective.

Davis, Eisenhardt et al. (2009) simulation – suggests entrepreneurial firms add structure and established firms stick to stable environments.

Adaptive approach is inferior to the planning approach contrary to the popular notion that adaptive is better for early stage entrepreneurship.

However finding a mentor with high network diversity can mitigate the disadvantages of using adaptive approach.

Important to examine processes of entrepreneurship through RCT to elicit causal inferences.

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